Regarding drug prescriptions, we have searched for datasets that could include either whole prescriptions (preferably speech data) and that would contain prescription information available in free text. Although not many, some datasets include drug prescriptions written in natural language. For example,  [1]} proposes a semi-supervised prescription extraction system based on information extraction data from medical reports [2]}. There are other challenges that include medical prescriptions mostly in narrative form inside EHRs such as I2B2 medication extraction challenge [3]} and Medication and Adverse Drug Events Challenge 2019 [4]}. Another source of prescriptions could be MedDialog dataset [5]}. It is composed of 0.26 million medical consultations in English and 1.1 million in Chinese scrapted from online platforms. Each dialogue contains a description of patient’s medical condition, a conversation between a patient and a physician and optionally diagnosis and treatment suggestions. However, the prescription part is not annotated and the dataset is only textual. To the best of our knowledge, there is no dataset of spoken drug prescriptions expressed in a natural way in any language. Therefore we aim to provide to the community a corpus with speech recordings, textual alignments and semantic annotations.
